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multi-fidelity modelling, your research will advance and integrate three core elements: (i) physics-based multi-fidelity structural models enabling high-resolution analysis at fatigue-prone hot-spots
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Number BAP-2026-482 Is the Job related to staff position within a Research Infrastructure? No Offer Description In the last decade, ML models taking inspiration from the brain and biological neurons have
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Position 1 - Hybrid Traffic Flow Modelling This PhD focuses on developing hybrid traffic flow models that combine physical modelling principles with machine learning approaches, such as Physics-Informed
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Aalborg University, Department of Energy, Campus Esbjerg, invites applications for a three-year PhD Stipend from October 1st or soon hereafter in dynamic modelling, simulation and optimization
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multi-fidelity modelling, your research will advance and integrate three core elements: (i) physics-based multi-fidelity structural models enabling high-resolution analysis at fatigue-prone hot-spots
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, with possibility of extension to 3 years in total) to strengthen our Pharmacometrics and Precision Dosing team. Research and Responsibilities Pharmacometric models, including preclinical pharmacokinetic
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Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg | Magdeburg, Sachsen Anhalt | Germany | 2 months ago
Systems is inviting applications for a PhD Student (f/m/d) position. Research topic: „Multi-scale Modeling of Biomolecular Phase Transitions“ The position is to be filled as soon as possible and is limited
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investigations and geochemical modelling. Specifically, you will: Characterise variability in mineralogical and petrophysical properties resulting from fluid–rock interactions under representative reservoir
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Application deadline: 30.09.26 Research theme: Applied Mathematics, Thermal-Fluid-Dynamics, Multi-Physics How to apply: https://uom.link/pgr-apply-2425 UK only This 4 year PhD project is fully funded and home students. The successful candidate will receive an annual tax-free stipend set at the...
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investigates the reproducibility of HP data processing pipelines using large language models (LLMs) to replicate published computational results. According to Starace et al. (2025), the state of the art in AI